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Strategic Cloud Engineer – GCP Platform & FinOps

Role overview

Qualifications

  • Strong expertise in Google Cloud Platform – GKE, Compute Engine, IAM, networking
  • Proven experience with Terraform in production environments
  • 3+ years managing production Kubernetes – cluster lifecycle and upgrades, ingress / reverse-proxy configuration, secrets and configuration management
  • Scripting in Python, Bash or similar

Responsibilities

  • GCP cost optimisation FinOps – rightsizing, autoscaling and workload efficiency; cost-observability dashboards
  • Kubernetes platform operations – cluster lifecycle, upgrades, node pools and scaling; multi-tenant SaaS customer lifecycle events
  • Infrastructure as code automation – own and evolve Terraform provisioning; automate customer provisioning and environment configuration
  • Platform services observability – troubleshooting distributed systems and production incidents

About the company

Ontrac Solutions logo

Ontrac Solutions

IT Services & IT Consulting

Ontrac Solutions specializes in engaging with organizations in bringing forward emerging technologies to enable, optimize and grow their businesses. We focus on building GenAI Platforms, Predictive Analytics, and Public Cloud Adoption.

Company details

IndustryIT Services & IT Consulting
Company size2 - 10

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Job description

We are seeking a Strategic Cloud Engineer to operate at the intersection of GCP FinOps (cost optimisation), Kubernetes platform engineering, operational excellence and agentic-AI-driven development.

This is a high-leverage engineering role responsible for optimising cloud spend, increasing platform reliability, and accelerating engineering output through automation and AI-assisted workflows. You will work across GCP, Kubernetes, Terraform and modern AI-assisted development environments. The environment is a high-scale, regulated, multi-product SaaS platform.

What you'll own

  • GCP cost optimisation & FinOps — rightsizing, autoscaling and workload efficiency; cost-observability dashboards (Grafana / BigQuery / billing exports); partnering with engineering teams to architect cost-efficient solutions
  • Kubernetes platform operations (GKE / multi-cluster) — cluster lifecycle, upgrades, node pools and scaling; ingress and domain routing; secrets, environment variables and service deployments; multi-tenant SaaS customer lifecycle events
  • Infrastructure as code & automation — own and evolve Terraform provisioning; support and optimise GitLab CI/CD rollout pipelines; automate customer provisioning and environment configuration
  • Platform services & observability — VictoriaMetrics, StatsD, Grafana, Google Cloud Monitoring, Elasticsearch / OpenSearch, Apache Airflow; troubleshooting distributed systems and production incidents
  • Global operations & reliability — instance provisioning and decommissioning, domain mapping, infrastructure support across providers including Hetzner, and participation in an on-call rotation
  • Agentic-AI engineering enablement — using AI-assisted tools (Cursor, OpenCode, multi-model AI development workflows) to accelerate infrastructure development, automate operational runbooks, and improve debugging of CI/CD pipelines and distributed systems

Core technical requirements

  • Strong expertise in Google Cloud Platform — GKE, Compute Engine, IAM, networking
  • Proven experience with Terraform in production environments
  • 3+ years managing production Kubernetes — cluster lifecycle and upgrades, ingress / reverse-proxy configuration, secrets and configuration management
  • Demonstrated ability to optimise cloud spend in production — cost allocation and usage patterns, rightsizing and scaling strategies, and building cost-visibility dashboards
  • GitLab CI/CD (preferred) or GitHub Actions, with the ability to debug pipelines and support release workflows
  • Grafana / VictoriaMetrics / StatsD / Google Cloud Monitoring; Elasticsearch / OpenSearch; Apache Airflow / Airbyte / n8n
  • Scripting in Python, Bash or similar
  • Agentic AI development (required baseline) — working familiarity with AI-native IDEs such as Cursor and agent-based development environments, and the ability to use AI to generate, review and optimise infrastructure code

Nice to have

  • Multi-cloud exposure (AWS / Azure)
  • Experience in regulated environments (SOC 2, ISO)
  • Exposure to European infrastructure providers (Hetzner)
  • Experience building internal developer platforms (IDP)

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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